Zi Humana Research is helping solve NP-hard combinatorial problems at the frontier of hybrid quantum-classical computing — QAOA sampling, classical refinement, and formal verification.
Combinatorial optimization — routing, scheduling, resource allocation, and network design — underpins logistics, finance, and infrastructure. This whitepaper describes a hybrid architecture in which NISQ QAOA generates candidate bitstrings, classical local search refines them, and SMT formal verification certifies hard constraints.
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View project →Open-access whitepaper — QAOA sampling, classical refinement, and SMT verification for NP-hard combinatorial problems.
View project →Formatted Hybrid-Quantum-Optimization.pdf — three-layer architecture, QAOA, and formal verification.
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A general architecture for hybrid quantum-classical optimization: a NISQ device generates candidate solutions via QAOA; a classical refinement stage repairs and improves those candidates through structure-aware local search; and a formal verification layer establishes logical guarantees over the constraints a solution must satisfy. Metrics include raw versus refined optimality ratio. Expository whitepaper — independent of any particular product or vendor.
| Layer | Function |
|---|---|
| Quantum sampling | QAOA / biased P_raw over {0,1}ⁿ |
| Classical refinement | Greedy bit-flip · configuration recovery · P_ref |
| Formal verification | SMT (Z3) — certificate or counterexample |
| Evaluation | R_raw · R_ref · Δ = R_ref − R_raw |
Figures and diagrams from the Hybrid Quantum Optimization research package — three-layer architecture, QAOA circuit, sample distributions, and pipeline flow.
Zi Humana Research · doi:10.5281/zenodo.22765909 · Author Zi R&D Center · Hybrid Quantum Optimization · NP-hard combinatorial optimization
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10.5281/zenodo.22765909